main purpose of current study is development of a new multi zone model for direct injection diesel engines. zone configuration is based on conical shape of spray. siebers’s correlation is used for spray cone angle calculation. experimental data are used for calculation of fuel inlet mass flow rate. fuel diffusion in different zones is calculated using fick’s law. a chemical kinetics mechanism c...

Facilitating citizens with accurate traffic flow prediction increases the quality of life. Roadside sensors and devices are used to capture live streams huge data Internet Things (IoT) is becoming popular for deployment effective Intelligent Transportation Systems (ITS). Traffic from datastreams require building a data-driven model. This challenging task has attracted researchers better interpr...

Abstract River flow prediction is a challenging problem due to highly nonlinear hydrological processes and high spatio-temporal variability. Here we present hybrid network of convolutional neural (CNN) long short-term memory (LSTM) for river prediction. The hybridization enables accurate identification the spatial temporal features in precipitation. A shortcut layer used as an additional channe...

Abstract Aiming at the problem that existing prediction models fail to utilize serial correlation, temporal correlation and spatial of data from multiple perspectives achieve accurate prediction, a dual-mode spatiotemporal graph convolutional neural network model combined with attention mechanism is proposed. This paper has been tested validated in very stochastic traffic forecasting. experimen...